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Lodestar

In-orbit robotic servicing for satellites

Graduate Software Engineer 3: State Estimation & Prediction

Applied Machine LearningUpdated on Nov 7
Full-timeLos Angeles, CA, USA$115k - $200k /yrIn-person

About the Job

Requirements

  • A Bachelor's, Master's, or PhD in Computer Science, Aerospace, Robotics, Applied Mathematics, or a related field, completed within the last 24 months or due to be completed before the start date.
  • Working proficiency in C++ and Python, demonstrated through coursework, research, internships, or personal projects.
  • Grounding in probabilistic state estimation, including Kalman filters, particle filters, or Bayesian inference, through coursework, research, or self-directed work.
  • Practical exposure to a deep learning framework such as PyTorch or TensorFlow, including sequence modelling such as seq2seq, RNNs, LSTMs, or Transformers.
  • Familiarity with trajectory modelling, multi-body dynamics, or orbital mechanics.
  • Ability to work through open-ended technical problems and communicate reasoning clearly.
  • To meet U.S. Government space technology export regulations, the candidate must be a U.S. citizen, lawful permanent resident of the U.S., protected individual as defined by 8 U.S.C. 1324b(a)(3), or eligible to obtain the required authorizations from the U.S. Department of State.

Responsibilities

  • Contribute to the design and implementation of core state estimation and prediction architecture for autonomous spacecraft operations.
  • Support research into novel estimation and prediction algorithms, from literature review through training and tuning to optimisation and deployment.
  • Implement, test, and benchmark classical and neural estimators that track the current state and trajectory of multiple dynamic targets in real time.
  • Build and evaluate neural models that forecast future trajectories and behavioural patterns of targets.
  • Assist in developing intent inference models that identify actions and dynamically rank threat levels.
  • Integrate state estimation and prediction models into mission simulation environments and autonomy decision systems.
  • Collaborate with cross-functional teams, including perception and on-board autonomy, to ensure prediction fidelity, robustness, and scalability across missions.

Desired Qualifications

  • Internship, industrial placement, or research assistantship in aerospace, robotics, estimation, or a related field.
  • A dissertation, thesis, or capstone project in state estimation, sensor fusion, or trajectory forecasting.
  • Experience applying sequence-to-sequence models to forecasting problems in dynamic environments.
  • Familiarity with sensor fusion techniques, such as combining radar, optical, and inertial data.
  • Exposure to GPU acceleration with CUDA or TensorRT for neural network training and inference.
  • Experience with Linux, Git, and CI/CD pipelines.
  • Familiarity with containerisation tools such as Docker and Kubernetes.
  • Awareness of real-time systems, multi-threading, and performance optimisation.
  • Understanding of networking and communication protocols for distributed autonomy systems.
  • Contributions to open-source projects or participation in student rocketry, CubeSat, robotics, or autonomous vehicle teams.

About the Company

Lodestar

In-orbit robotic servicing for satellites

Lodestar Space builds space robotics services that inspect, protect, and repair satellites and orbital infrastructure with a modular, dexterous robotic arm. The arm operates in harsh space environments and uses supervised autonomy guided by a computer-vision system and a proprietary neural network to interact with both cooperative and uncooperative targets without a fixed parts catalog. The platform-agnostic design lets the arm integrate with any launch provider or spacecraft, enabling in-orbit servicing across customers and missions. The goal is to extend satellite lifespans, protect assets, and support space infrastructure by delivering reliable autonomous manipulation capabilities for orbital operations.

Company size
11-50
Company stage
Grant
Total funding
$2.5M
Headquarters
Newington, United Kingdom
Founded
2023

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